Driver psychic state analysis based on EEG signals

Title:

Driver psychic state analysis based on EEG signals

Creator:

Faber, Josef, Novák , Mirko, Tichý , Tomáš, Svoboda , Petr, and Tatarinov , Vladimír

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:8f66409f-2b91-4603-897d-92510f73f7e7
uuid:8f66409f-2b91-4603-897d-92510f73f7e7

Subject:

vigilance, attention, car-driver interaction reliability, and EEG analysis

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

EEG activities with open eyes in a quiet state (OA), during pseudo-Raven's test (PRA), in a hypnagogic state (HYP) and REM sleep (REM) are marked by similar, nearly flat curves. Further we observed states with eyes closed (OC), with hyperventilation (HV), with calculation (CAL) and in NONREM 1 sleep (NR 1). During OA, the EEG spectrum contains some delta and but rudimental alpha activity while during PRA and in HY there is an increase in delta-theta and a significant decrease in alpha activities. Hence, not even Fast Fourier Transformation (FFT) can differentiate between the states with fkat curves. This made us introduce another EEG curve analysis for coherence function (CF). We investigated 24 healthy volunteers aged 22 -- 55 years, 19 men and 5 women, in the above mentioned eight states with simultaneous EEG recording. Vigilance was controlled by means of acoustic stimulation, reactivity was expressed in reaction time (ReT), i.e. latency of response in milliseconds (ms). Imitation Raven's test (pseudo-Raven' = PRA) was used for psychic testing. Recorded in the afternoon hours after partial sleep deprivation, the EEG curve was described optically using FFT and CF as well. FFT results have already been mentioned above. CF showed lower values during OA with up to 400 ms of ReT, a diffuse increase during HYP with ReT of 800 - 1200 ms, and a multifocal rise of delta activity in the EEG curve during PRA. Consequently, EEG analysis can help differentiate between the above eight states, otherwise barely distinguishable with the naked eye especially in cases with flat EEG curves. Using similar analyses, it is possible to discriminate all stages of NONREM and REM sleep without polysomnography.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2006 Volume:16 | Number:1

Harvested from:

CDK

Metadata only:

false